1. Technical Field
The present teaching relates to surgical procedure assistance. More specifically, the present teaching is directed methods, systems, and programming for estimating a deflated lung shape in video assisted thoracic surgery.
2. Discussion of Technical Background
In minimally invasive thoracic surgery, patients are pre-scanned with a computed tomography (CT) image. Surgical planning is then performed based on the CT images. Three-dimensional (3D) models of anatomical structures may be built from the CT images. Such models may include, but not limited to, models of a 3D lung, a 3D airway, a 3D vessel, a lung lobe fissure, and a tumor. A lesion resection plan may be generated based on the 3D models. A typical resection plan may include where the incision line is, how much safety margin may be put around the tumor, how a critical anatomical structure, such as lung fissures, may be avoided. Quantitative information may include, but not limited to, the distances of the tumor to critical anatomies, distances of the resection surface to critical anatomies, the depth on resection surface from the incision line. Due to its minimally invasive nature, the Video Assisted Thoracic Surgery (VATS) has become widely adopted. During VATS, a tiny video camera and surgical instruments are inserted into the patient's chest. Through looking at the images transmitted to a display monitor, the surgeon performs the procedures, such as lesion resection. At the time of surgery, however, the lung is made collapsed. That is, part of air is let out of the lung. Due to the shape change of the lung, the pre-surgical plan obtained using the pre-operative CT images may no longer be applicable. For example, the distance of the tumor to the lung surface is no longer the same as that computed from pre-surgical planning. On the other hand, it may not be practical to perform another CT scan during the VATS procedure. Therefore, there is a need to provide an improved solution to solve the above-mentioned problems.